Magazine article Information Today

Finding the Keys to Library Prosperity

Magazine article Information Today

Finding the Keys to Library Prosperity

Article excerpt

The networking of our lives through the web has created a new species of data users. Not just for libraries, but for almost anyone seeking information about practically anything quantifiable, anywhere--such as data from smart tractors plowing the Argentine pampas using mobile GPS, StatsCast reckonings of the spin rate of a World Series curveball, or a satellite's-eye-view rate of glacier melts in Antarctica--we're all swimming in a sea of data.

The Internet of Things is just around the corner, and that's when it will get really interesting. We'll have a tsunami of data coming off millions of smart sensors (as if we don't have enough of the stuff already). The business pages these days are chock-full of Big Data stories, but the real action isn't all in Google's massive data centers and Airbnb and Uber's algorithms; it's in real-time, contextualized data you can use "hyperlocally," meaning, right on your doorstep.

For libraries and the communities they serve, hyperlocal data is rapidly becoming a currency, such as for the 10-year-old South Asian French immersion student, the retired nurse and mompreneur, and the regional tourism director seeking new markets. Every community has folks knocking on library doors with an insatiable hunger for data.

So what's the future of libraries as the community hunger for "small," local data drives new skills acquisitions for the most accessible and visible "data hackers" in town: your librarians? That's exactly what some of the biggest thinkers on the planet addressed when they took a huge (as in cosmic) look at data science for librarians from their own unique point of view: infinity.

Why huge? Because they're astrophysicists, and they contend with galaxies of data from over eons of time. In his remarkable blog, The Library Lab (bit.ly/liKglrN), Christian Lauersen, director of the Royal Library's Faculty Library of Social Sciences in Copenhagen, Denmark, posted about Data Scientist Training for Librarians (DST4L), an experimental curriculum that evolved at the Harvard-Smithsonian Center for Astrophysics' John G. Wolbach Library. I caught up with Lauersen via email and then touched base with Thunder Bay (Ontario) Public Library's data-sawy CEO and chief librarian, John Pateman, who moved to Canada from the U.K. because of that country's current austerity campaign.

More Than Survival

So why are astrophysicists involved with data science for librarians? Because the Harvard-Smithsonian Center for Astrophysics recognized a knowledge-to-action gap between what librarians know and what they can do for their communities' growing appetite for data. For both Lauersen and Pateman, one of the most powerful responses librarians can have for digital disruption is to mediate between uncontextualized data and the highly specific needs of their community.

For Lauersen, librarians stand to benefit in multiple ways by adopting the DST4L toolkit. "We will see a whole new type of data native users starting to use libraries the next couple of years," he predicts. "The demands of those users will [affect] not only libraries but our whole society. For libraries, this is [a] platform that will create value. And it's actually not such a new thing. We've been working with supporting information literacy for many, many years."

Lauersen, who attended the DST4L training course in Copenhagen in September, recalls the 3-day toolkit-driven event was dedicated to an intense, get-your-hands-dirty process of playing with data archiving, sharing, and analytics. "The real data currency, as I see it, is knowing how to handle, wrangle and analyze all this data," says Lauersen. "That's how libraries should respond to this development: providing skills, methods and tools to the people who work with data. Don't catch the fish for them but teach them how to fish. Like libraries [have] been doing forever when it comes to information seeking. It's all about data literacy. …

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